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whisper-small-tunacad-lora – AI Model by fatmabesdouri96 | AlphaNeural AI
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whisper-small-tunacad-lora
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peft
safetensors
adapter
lora
transformers
openai/whisper-small
apache-2.0
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whisper-small-tunacad-lora
This model is a fine-tuned version of
openai/whisper-small
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.8236
Wer: 1.8713
Cer: 1.3979
Mer: 0.9589
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
learning_rate: 0.001
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 32
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 100
num_epochs: 3
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
Cer
Mer
10.9010
1.0
76
1.0632
2.1048
1.6157
0.9577
6.2805
2.0
152
0.8659
1.7692
1.3103
0.9635
3.6087
3.0
228
0.8236
1.8713
1.3979
0.9589
Framework versions
PEFT 0.18.1
Transformers 5.0.0
Pytorch 2.10.0+cu128
Datasets 4.8.3
Tokenizers 0.22.2
